ShadowDancer: Teaching Video World Models Any Action by Learning Unified Dynamics Representations from a Video and Its Shadow

ShadowDancer enables frame-level control of video world models by learning unified dynamics representations from video-shadow pairs. By training on videos that replay identical dynamics under varying appearances, the method decouples physical motion from visual style. This allows for any-action control that transfers across diverse scenes and environments.